Part 3: Emerging Technologies:

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Since the appearance of railways and canals, industrial revolutions have been characterized by the transformation of physical infrastructure networks as much as by production methods. Now the Fourth Industrial Revolution (4IR) is shaking up the interdependent set of critical physical infrastructure networks on which we all depend, including transport (road, rail, waterways, airports); energy (electricity, heat, fuel supply: gas, liquid and solid); digital communications (fixed, mobile); water (supply, waste water treatment, flood protection); and solid waste (collection, treatment, disposal). This process brings huge opportunities for innovation, but also complex risks.

The Economic Characteristics of Infrastructure Networks

The value of a physical infrastructure network increases with its scope. In communications (transport, digital), the more people a network connects, the more useful it becomes. In resource networks (energy, water), connecting more people can help build resilience and leverage economies of scale. Costs are high relative to returns in the early stages of building a network, and also later when connecting geographically remote areas with low population density: extending coverage to such areas usually requires government intervention, although 4IR technologies may shake up that economic logic by drastically cutting the costs of connectivity.

Because physical infrastructure networks are often natural monopolies as a result of barriers to entry, the public sector typically either provides those barriers or regulates them on behalf of their users. Regulators have to tread the delicate line between setting affordable tariffs and ensuring that capital can be found to invest in maintaining and renewing networks. The pendulum has swung between private and public capital funding of infrastructure: for example, private financiers backed the creation of railway networks in Europe and North America in the 19th century, some losing their shirts. But much of today’s ageing physical infrastructure in advanced economies was built with public funding during the 20th century. Britain led the way in utility privatization in the 1980s and 1990s, and it has generally improved asset management and reduced costs for customers. On the other hand, private finance has typically shied away from large and risky new assets, such as nuclear reactors. Uncertainties related to the 4IR play a part in that reluctance.

With tight public finances, governments and regulators are having to devise mechanisms for leveraging private finance while seeking to avoid the inflexibility and questions over value for money that have dogged public-private infrastructure finance in the past. It is still unclear how the enormous investment needs for some kinds of infrastructure are going to be met.

The Revolution

Electricity powered the Second and Third Industrial Revolutions, as networks achieved economies of scale by connecting large plants over high-voltage transmission grids to local distribution networks reaching many users. This aggregation of users helped to smooth out much of the local variation in demand, so steady-running base-load plants could be the workhorses of the network, with extra capacity patched in to deal with daily and seasonal peaks. Prohibitively high barriers to entry meant there was little competitive pressure to reduce the significant amount of energy lost as waste heat in the generation, transmission and distribution of electricity.

All of that is now changing. Collapsing prices of photo-voltaic cells make solar panels price-competitive with large-scale generation (Figure 3.3.1). The cost of offshore wind is also dropping fast, with firms such as DONG Energy and Vattenfall bidding prices down as low as €60 per Megawatt hour. Innovation in storage technology is helping with intermittency challenges – from large-scale storage to household battery units and plugged-in electric vehicles, which will provide an additional buffer. The 4IR is moving electricity networks away from needing to be large-scale, top-down systems.

Technological innovations will increasingly offer households and firms the possibility of going “off-grid” entirely – but even if they increasingly generate their own power, most are still likely to want to remain connected to the high-voltage networks that are the backbone of today’s electricity supply systems. Indeed, the rising use of solar, wind and tide power – with their associated intermittency issues and their greater need to tap the energy storage possibilities of hydropower in mountainous regions – will increase the appeal of high-voltage connections over long distances. But the growing scope for businesses and homes to supply and store their own electricity will make electricity networks multi-scale and less “lumpy” in terms of their capital requirements.

Beyond supply and storage, technology is improving efficiency by integrating supply and demand. Until very recently, energy suppliers and network operators have had to rely on crude methods to forecast demand for electricity. Big data, pervasive sensors and the Internet of Things are making it easier for users to monitor and control their energy demand, and for grids to predict and manage energy supply. In a world of prosumers and distributed suppliers, the challenges are how to synchronize supply and demand and pay for resilience.

Water could also transition from centralized networks towards more distributed systems. New materials and sensor technologies allow treatment at the household or community level, creating opportunities to harvest rainwater and directly reuse waste water. For the time being, economies of scale still favour large, centralized plants in existing urban areas: they also allow utilities to monitor water quality centrally and address failures quickly. Relying on localized water storage would also create challenges in prolonged periods of drought. But centralized networks are costly to create, and the balance of costs and benefits is beginning to tip in favour of distributed water systems if cities can be planned for these systems from the outset.

Regarding communications, the 4IR will continue to shift the balance between mobile and fixed networks. To improve mobile broadband, 5G technologies are envisaged to provide much faster data transfer (>1 Gigabyte per second) and reduced end-to-end latency (sub-1ms). By consolidating existing layers of technology, such as 2G, 3G, 4G and Wi-Fi, 5G will also improve coverage and ‘always-on’ reliability – it is an ensemble of different technologies, rather than a single type of new technology. Although the experience of those previous technologies suggests that new uses for 5G will emerge after deployment, two key roles are already anticipated for 5G: providing gigabit connectivity for businesses and consumers for a range of content, applications and services (the top of the pyramid); and enabling ultra-reliable, low latency machine-to-machine (M2M) communication (the bottom of the pyramid), which will help to achieve objectives in other infrastructure systems, such as easing congestion (Figure 3.3.2).

Governments are facing a difficult decision about whether to be first movers in rolling out 5G or wait to learn lessons from first movers, in the expectation that costs will decrease. For now, the bandwidth of fibre-optic cables remains hard to beat – but it is also expensive in towns and cities: 80% of the costs are attached not to the technology itself but to the labour-intensive process of digging trenches and laying ducts. Uncertainty about future technological development can inhibit investment: is it better to dig trenches for cables or wait for 5G? The same dilemma applies to other types of infrastructure – for example, in the time it takes to roll out smart metres, new and better metres are being developed.

While improving some infrastructure assets, the 4IR promises to ease pressure on others by finding alternative ways to deliver the same functionality. For example, meeting in virtual reality is becoming an increasingly acceptable substitute for physical business travel, while drones may substitute for delivery vans in cities. Satellite technologies will help to fill the gaps in digital connectivity where fixed or terrestrial mobile technologies are not cost-effective. Where energy companies once defined themselves by their physical infrastructure assets, they increasingly see themselves as being in the business of providing specific services such as heating and lighting. As the 4IR creates new ways to deliver services, it may begin to challenge whether infrastructure should be seen as a special category at all.

The Risks

In theory, greater connectivity brings intrinsic resilience: electricity networks with more supply points, for example, should be less prone to failure. However, as different infrastructure networks become more interdependent, there is also growing scope for systemic failures to cascade across networks and affect society in multiple ways. In particular, electricity networks are now assuming an increasingly central role in many areas of life, such as road transportation and heating (taking over from gas and liquid fuels).

Systemic risks can come from many directions – whether these are cyberattacks or software glitches, solar storms or even just unexpectedly widespread and persistent clouds – and the increased complexity bring brought about by the 4IR makes the severity of those risks very difficult to estimate (Box 3.3.1). Society is increasingly dependent on information and communication technology networks in particular, and these have their own dependencies and vulnerabilities. In a 20th-century electricity network, it is possible to analyse the consequences of any given sub-station failing. That becomes impossible when every household is supplying and storing electricity and constantly adapting how much it uses based on price signals: we may suspect that our networks are acceptably resilient, but we cannot model them accurately enough to be sure.

Because the 4IR intensifies networks’ reliance on each other, there is a need for information sharing – utility providers tend to understand their own systems well, while often being more or less in the dark about the resilience of the systems to which they are connected. However, concerns about commercial confidentiality and security increase the challenge of developing protocols for information sharing that would help dependent customers to understand their risks. Not only infrastructure providers but also businesses need to understand risks and resilience more fully: analysis of supply chain risk tends to focus more on physical sites than the infrastructure networks that sustain those sites and move goods and services between them.

Box 3.3.1: Mapping Infrastructure Vulnerability to Natural Hazards

An “infrastructure criticality hotspot” is defined as a geographical location where there is a concentration of critical infrastructure, measured according to the number of customers directly or indirectly dependent upon it. In the map of China below, red spots indicate where the highest numbers of people and businesses would be affected if a natural disaster caused infrastructure failure. According to this research, from the Environmental Change Institute at the University of Oxford, China’s top infrastructure hotspots are Beijing, Tianjin, Jiangsu, Shanghai and Zhejiang.

Given the scale of China’s manufacturing production and its role in the global supply chain, the business impacts of natural disasters could be astronomical: flooding in the more economically developed coastal provinces already accounts for more than 60% of the country’s losses due to flooding.1-a The Oxford study finds that severe flooding events could disrupt infrastructure (rail, aviation, shipping and water) services for an average of 103 million people, while drought could affect an average of 6 million electricity users.

Source: Hu et al. 2016

Governance of Infrastructure Networks in the 4IR

Like infrastructure networks themselves, arrangements for their governance have evolved incrementally and mostly siloed by sector – not least because ownership arrangements can be so different, ranging from highly competitive privatized markets (e.g. in mobile phone provision) through regulated monopolies, public-private partnerships, state-owned enterprises and direct public provision.1

Governments are increasingly recognizing that this fragmented approach is becoming unfit for purpose in the 4IR. As networks become interconnected – for example, as digital technologies enable the routing of vehicles and the management of electricity and water demand – a “system-of-systems” approach to governance is needed. That requires appropriate sharing of information among network operators, and also requires regulators adopting common principles across networks.

Just as network operators and businesses need to better understand and manage systemic risks, governments and regulators need to take a wider view. Examples of new governance structures that recognize the need for a more integrated approach include the National Infrastructure Commission in the United Kingdom, Infrastructure Australia, and the National Infrastructure Unit in New Zealand. These new entities are having to navigate tensions between taking a national-level strategic approach to articulating needs for infrastructure to support growth and productivity and creating space for competition and innovation.

While the 4IR is creating complex new challenges for planners and regulators, it is also providing powerful new tools for monitoring and analysing system performance at hitherto unprecedented spatial and temporal scales – and testing resilience through simulation. Modelling exercises in a virtual environment will never give infallible results, but in itself the exercise of constructing and testing models can help to expose vulnerabilities in system resilience. Alongside their traditional role of minimizing the harmful effects of natural monopolies, infrastructure regulators in the 4IR should be paying more attention to systemic risks, building technical capabilities and standards for information sharing and stress testing.

Chapter 3.3 was contributed by Jim Hall, Oxford Martin School, University of Oxford.